Informatica World Tour India: The Magic of Thinking Big – From Data to Profit
As organizations wake up to the dawn of endless possibilities of value creation from big data, they are also faced with the challenge of deriving value from actionable, accessible, and secure data. From growing transactional information to vast reservoirs of social media data, from long-neglected unstructured content to real-time data streams taken from sensors and devices, big data presents both a business opportunity and an IT challenge for organizations in virtually every industry.
While most IT decision-makers view big data projects as a way to improve operational efficiency and agility, many see opportunities to deliver new products and services and increase customer acquisition and retention by taking advantage of big data. However, the path of implementation is strewn with multifarious challenges. Mining the data requires highly skilled analytical talent capable of translating massive data into actionable insights that lead to tangible business results. Dearth of big data resources, scarcity of used case scenarios and difficult and time-consuming implementation were the underpinning of an insightful panel discussion titled “The Magic of Thinking Big – From Data to Profit” at the Informatica World Tour India, held in Mumbai recently. The high power panel comprised Tony Young, Senior Vice President and Chief Information Officer, Informatica; Arun Dhall, Head of Decision Support System, the Enterprise Data Warehouse and BI division of Reliance; and Soumendra Mohanty, Partner and Global Lead-Information Management, Analytics and Big Data, Accenture.
In his opening remarks, Tony Young brought to light the obstacles that companies wanting to transform their business through big data face. One of the most serious challenges that exist in the market today is a shortage of specialized skillsets that can unlock the value of big data. You need people who can demystify the data and take a holistic view of it. There are also challenges relating to data quality and data governance. It is important to have good practices around people and processes, as well as the right set of enabling technologies,” he explained.